# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import datetime import pandas as pd from sqlalchemy import BigInteger, Date, inspect, String from sqlalchemy.sql import column import superset.utils.database as database_utils from superset import db from superset.connectors.sqla.models import SqlMetric from superset.models.slice import Slice from .helpers import ( get_example_data, get_slice_json, get_table_connector_registry, merge_slice, misc_dash_slices, ) def load_country_map_data(only_metadata: bool = False, force: bool = False) -> None: """Loading data for map with country map""" tbl_name = "birth_france_by_region" database = database_utils.get_example_database() engine = database.get_sqla_engine() schema = inspect(engine).default_schema_name table_exists = database.has_table_by_name(tbl_name) if not only_metadata and (not table_exists or force): csv_bytes = get_example_data( "birth_france_data_for_country_map.csv", is_gzip=False, make_bytes=True ) data = pd.read_csv(csv_bytes, encoding="utf-8") data["dttm"] = datetime.datetime.now().date() data.to_sql( tbl_name, engine, schema=schema, if_exists="replace", chunksize=500, dtype={ "DEPT_ID": String(10), "2003": BigInteger, "2004": BigInteger, "2005": BigInteger, "2006": BigInteger, "2007": BigInteger, "2008": BigInteger, "2009": BigInteger, "2010": BigInteger, "2011": BigInteger, "2012": BigInteger, "2013": BigInteger, "2014": BigInteger, "dttm": Date(), }, index=False, ) print("Done loading table!") print("-" * 80) print("Creating table reference") table = get_table_connector_registry() obj = db.session.query(table).filter_by(table_name=tbl_name).first() if not obj: obj = table(table_name=tbl_name, schema=schema) obj.main_dttm_col = "dttm" obj.database = database obj.filter_select_enabled = True if not any(col.metric_name == "avg__2004" for col in obj.metrics): col = str(column("2004").compile(db.engine)) obj.metrics.append(SqlMetric(metric_name="avg__2004", expression=f"AVG({col})")) db.session.merge(obj) db.session.commit() obj.fetch_metadata() tbl = obj slice_data = { "granularity_sqla": "", "since": "", "until": "", "viz_type": "country_map", "entity": "DEPT_ID", "metric": { "expressionType": "SIMPLE", "column": {"type": "INT", "column_name": "2004"}, "aggregate": "AVG", "label": "Boys", "optionName": "metric_112342", }, "row_limit": 500000, "select_country": "france", } print("Creating a slice") slc = Slice( slice_name="Birth in France by department in 2016", viz_type="country_map", datasource_type="table", datasource_id=tbl.id, params=get_slice_json(slice_data), ) misc_dash_slices.add(slc.slice_name) merge_slice(slc)